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Register a new user(Guided Local Search- Tabu Search) Hybrid Algorithm Integrated With Simulated Annealing Algorithm To Solve The Vehicle Routing Problem With Time Windows
تكامل الخوارزمية الهجينة ( البحث المحلي الموجه - البحث المحظور ) مع خوارزمية محاكاة التعدين للمساهمة في حل مسألة توجيه المركبة مع نوافذ زمنية
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ندرس في هذا البحث إمكانية المساهمة في حل مسألة توجيه المركبة مع نوافذ زمنية ، و ىي واحدة من مشاكل الأمثمية من النوع NP-hard حيث أخذت كثيرا من اهتمام الباحثين في الوقت الحاضر بسبب تطبيقاتها ذات الطابع اليومي ، إذ لا توجد حتى الآن خوارزمية تقدم الحل الأمثل لهذه المشكلة بسبب تعقيد زمن كثيرة الحدود و هذا يعني أن زمن الحل لمسألة توجيه المركبة مع نوافذ زمنية ينمو باطراد مع زيادة عدد العقد و كل الخوارزميات المستخدمة تعطي حلولاً تقريبية .
In this research, we are studying the possibility of contribution in solving the Vehicle Routing Problem With Time Windows(VRPWTW), that is one of the optimization problems of the NP-hard type. This problem has attracted a lot of attention now because of its real life applications. However, there is still no algorithm that provides us with the perfect solution to this problem because of the complexity of polynomial time. This means that the time of the solution to the VRPWTW is growing steadily with the increase in the number of nodes .All the used algorithms have just given solutions that are close to the optimal one.
References used
BORTFELDT,A., HAHN ,T., MANNEL, D., MONCH,L., 2015-Hybrid algorithms for the vehicle routing problem with clustered backhauls and 3D loading constraints. European Journal of Operational Research, 243(1) :85–96
AZI,N., GENDREAU, M., POTVIN J.-Y, 2014- An adaptive large neighborhood search for a vehicle routing problem with multiple routes. Computers & Operations Research,41:167–173
ARCHETTI,C.,SPERANZA,G.,2014-A survey on matheuristics for routing problem. EURO Journal on Computational Optimization, 2 :235–246
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In this research, we are studying the possibility of contribution in solving the Vehicle
Routing Problem with Time Windows(VRPTW),that is one of the optimization problems
of the NP-hard type.
Moreover, Hybrid algorithm (HA) provided that integrate
s between Tabu Search
Algorithm and Guided Local Search algorithm And existence 2- Opt Local Search, based
on the savings algorithm in terms of continued of a particular objective to provide a lot of
savings. As we will compare the presented approach with standard tests to demonstrate
the efficiency, and their impact on the quality of the solution in terms of speed of
convergence and the ability to find better solutions.
In this research, we are studying the possibility of contribution in solving the Vehicle Routing Problem With Time Windows(VRPWTW), that is one of the optimization problems of the NP-hard type. This problem has attracted a lot of attention at the pre
sent time because of its real life applications. However, there is still no algorithm that provides us with the perfect solution to this problem because of the complexity of polynomial time. This means that the time of the solution to the Vehicle VRPWTW is growing steadily with the increase in the number of nodes .All the used algorithms have given solutions that are close to the optimal one . We'll introduce two algorithms , the first is Improved Ant Colony System algorithm (IACS) that is capable of searching multiple search areas simultaneously in the solution space is good in diversification ,and the second Simulated Annealing algorithm (SA) is a local search technique that has been successfully applied to many NP-hard problems. Moreover, we will present the In this research Hybrid algorithm (HA) Hybrid Algorithm provided (IACS-SA) that integrate between improved ant algorithm and Simulated Annealing algorithm . We will known standard tests are given to demonstrate the applicability and efficiency of the presented approach and comparisons with other available results are presented.
In this research, we are studying the possibility of contribution
in solving the multi-objective vehicle Routing problem with time
windows , that is one of the optimization problems of the NP-hard
type , This problem has attracted a lot of attenti
on now because of
its real life applications.
Moreover, We will also introduced an algorithm called hybrid
algorithm (HA) which depends on integrates between Multiple
objective ant colony optimisation (MOACO) and tabu search (TS)
algorithm based on the Pareto optimization , and compare the
presented approach is the developer with standard tests to
demonstrate the applicability and efficiency.
n this research, we are studying the possibility of contribution in solving the Vehicle Routing Problem (VRP), which is one of the optimization problems that, because of its Real Life applications, has attracted a lot of attention at the present tim
e. It is a problem of the NP-hard type. However, because of the complication of polynomial time there is still no algorithm providing us with the optimal solution of this problem. All the used algorithms give solutions that are close to the optimal one .
In this research, we will present the Hybrid Algorithm (HA) in two phases .In the first phase the Sweep Algorithm (SW) is applied, and in the second one the Ant Colony Algorithm and the local search 3-opt are applied. we will then compare the quality of the solution resulted from this hybrid approach with the results of well-known standard tests to determine the effectiveness of the presented approach .
We study in this paper the possibility of contribution in solving the vehicle routing problem (VRP) by using the improved ant colony system ( IACS) , which is one of the optimization problems that, because of its Real Life applications, has attracted
a lot of attention at the present time. It is a problem of the NP-hard type. However, because of the complication of polynomial time there is still no algorithm providing us with the optimal solution of this problem. All the used algorithms give solutions that are close to the optimal one .
We present the improved ant colony system algorithm that, based on ant colony system algorithm, possesses a new state transition rule, a new pheromone updating rule and diverse local search approaches .
The experimental results of the proposed ( IACS) algorithm compared with the results of well-known standard tests show that our IACS yields better solutions than the other ant algorithms in the literature and is competitive with other meta-heuristic approaches in terms of quality(run time and number of good solutions ).
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